Activepieces: Complete Platform Profile
Activepieces is an open-source workflow automation platform — the most technically capable open-source alternative to Zapier and Make — with native AI agent capabilities built into its flow builder. Founded in 2022 by Mohammed Abualrob and Shayaan Ahmed (Y Combinator W23), Activepieces was created to address a specific frustration: powerful automation should not be locked behind expensive SaaS subscriptions, and teams should be able to self-host their automation infrastructure with full data control.
The platform ships as a TypeScript application that can be deployed on any server or container infrastructure, and as a managed cloud service. It offers more than 200 app integrations, a visual drag-and-drop flow builder, an AI piece library for LLM integration, and an active open-source community contributing new pieces and features. For broader context on the automation and agent platform landscape, see the AI Agents profiles directory.
Overview#
Activepieces sits at the convergence of two trends: the push to bring automation out of expensive proprietary SaaS platforms (the "open-source Zapier" movement) and the integration of LLMs into workflow automation. The platform was purpose-built to be self-hostable from day one — not as an afterthought but as a core architectural decision that shapes everything from the data model to the deployment story.
The "open-source Zapier alternative" positioning is accurate but undersells what Activepieces is evolving toward. The platform now includes AI pieces for GPT-4o, Claude, Gemini, and other models; an AI agent piece that implements an autonomous agent loop; and a growing library of AI-specific actions for common LLM tasks (text generation, classification, extraction, summarization). This AI layer transforms Activepieces from a pure automation tool into a platform where AI actions and traditional app integrations can be combined in a single workflow.
The platform competes with Zapier and Make for traditional automation, and increasingly with tools like n8n (the dominant self-hosted automation platform) and tools like Lindy AI (AI-native automation). Understanding where Activepieces sits relative to these alternatives is covered in our n8n vs Make vs Zapier comparison.
Activepieces is fully open-source under the MIT license, meaning there are no licensing fees for self-hosted deployment and no vendor lock-in on the platform itself. The commercial model is cloud hosting and (eventually) enterprise features for organizations that want managed infrastructure.
Core Features#
Visual Flow Builder#
The Activepieces flow builder uses a step-by-step, vertical canvas design (rather than a horizontal node graph). Each flow consists of a trigger and a sequence of actions. Flows support: conditional branching (if/else based on data values), loops (iterate over arrays, process each item in sequence), parallel branches (run multiple action sequences simultaneously), and delay steps (wait for a specified time or until a condition is met).
This design is more opinionated than n8n's free-form canvas — some users find it more readable, others miss the flexibility of free-form positioning. Complex flows with many branches can become long scrolling sequences that require discipline to organize.
Pieces Library (200+ Integrations)#
Activepieces calls its integrations "pieces." The library includes more than 200 pieces covering major SaaS categories: productivity (Google Workspace, Microsoft 365, Notion, Airtable), CRM (HubSpot, Salesforce, Pipedrive), communication (Slack, Discord, Telegram, email via SMTP), e-commerce (Shopify, WooCommerce), marketing (Mailchimp, ActiveCampaign), and developer tools (GitHub, GitLab, Jira, Linear).
Pieces are community-contributed via a TypeScript SDK. Writing a new piece requires implementing a small TypeScript module with a defined schema for authentication, triggers, and actions. The contribution process is simpler than building a Zapier app or Make module, which drives a faster-growing integration catalog. New pieces are accepted via GitHub pull request and published to the community registry.
AI Pieces and Agent Capability#
The AI pieces are Activepieces' most rapidly growing area. Current AI pieces include: AI Text (generate text using GPT-4o, Claude, Gemini, or custom OpenAI-compatible endpoints), AI Extract (extract structured data from unstructured text), AI Classify (categorize text into predefined classes), AI Summarize (generate summaries), Image Generation (Stable Diffusion, DALL-E), and AI Agent (an autonomous agent that uses tools and iterates to complete a goal).
The AI Agent piece is the most significant for teams interested in AI-native automation. It implements a standard agent loop — the agent receives a goal, chooses from available tools (which can include other Activepieces actions), takes action, observes the result, and iterates until the goal is complete or a step limit is reached. Tools available to the agent can be standard Activepieces pieces or custom HTTP actions.
This architecture allows building agents that combine AI reasoning with direct integration to business systems — for example, an agent that receives a support request, searches a knowledge base, checks the customer's order history in Shopify, drafts a response, and sends it via email — all within a single Activepieces flow.
Webhook and HTTP Triggers#
Activepieces supports webhook triggers (receive HTTP POST requests and start a flow), allowing external systems to kick off automation flows without a native piece integration. Combined with the HTTP Request action (make arbitrary HTTP calls), this provides a path to integrate with any system that has an API, regardless of whether a native piece exists.
Scheduled triggers (cron-based) allow flows to run on a time schedule. Polling triggers (checking for new data at intervals) are used for pieces that don't support webhooks.
Self-Hosting Architecture#
Activepieces is distributed as Docker images. The standard deployment consists of the main application server, a PostgreSQL database, and a Redis instance for queue management. The application can be deployed on any server, VPS, or cloud infrastructure (AWS, GCP, Azure, DigitalOcean, Hetzner). Official Docker Compose configurations are provided for single-server deployments; Kubernetes manifests are available for high-availability deployments.
Data residency is complete — no flow data, trigger payloads, or execution logs leave the self-hosted infrastructure (unless explicitly sent to an external AI API for processing). API keys for third-party services are stored encrypted in the local PostgreSQL database.
This self-hosting capability is the primary reason teams choose Activepieces over Zapier or Make for sensitive data handling. Teams automating workflows involving PII, financial data, or proprietary business information can keep all flow data within their own infrastructure.
Multi-Tenant and White-Label Support#
Activepieces supports multi-tenancy — running a single deployment that serves multiple separate organizations (projects), each with isolated flows, credentials, and execution logs. This makes it suitable for agencies building automation solutions for multiple clients, or enterprises needing project-level isolation.
White-label support allows rebranding the Activepieces interface with custom logos, domain, and color schemes — relevant for agencies or SaaS companies embedding automation as a feature in their own product.
Pricing & Plans#
Open Source (Self-Hosted): Free, MIT license. Full platform functionality, no seat limits, no flow limits, no execution limits beyond your infrastructure capacity. Requires self-hosting infrastructure management.
Activepieces Cloud Free: Limited to a small number of tasks per month (currently 1,000 tasks/month) across unlimited flows. Suitable for light personal use or evaluation.
Activepieces Cloud Pro: Approximately $49/month for 50,000 tasks/month. Includes all integrations, unlimited flows, priority support, and advanced step types. Appropriate for small teams with moderate automation volume.
Activepieces Cloud Business: Approximately $99/month for 150,000 tasks/month. Adds team collaboration features, higher task limits, and custom pieces support.
Cloud Enterprise / Managed Self-Hosting: Custom pricing for large organizations. Includes dedicated infrastructure, SLA guarantees, professional onboarding, and custom integration development.
A "task" in Activepieces is one action execution within a flow. A flow with 5 action steps that runs 1,000 times consumes 5,000 tasks. High-volume automations should model task consumption carefully before selecting a cloud plan.
Strengths#
Genuine open-source with MIT license. Unlike some "open-core" platforms with restrictive licenses on key features, Activepieces' MIT license allows unrestricted self-hosted use. Teams can deploy, modify, and redistribute without license complexity.
Active development and community contribution pace. The Activepieces GitHub repository has one of the most active contribution rates in the open-source automation space. New pieces, bug fixes, and features ship at a rapid pace driven by both the core team and community contributors.
AI integration is first-class, not an afterthought. The AI pieces and AI Agent capability were designed as core platform features rather than bolt-on additions. This reflects the team's view that automation and AI are converging, and positions Activepieces ahead of pure automation tools that are adding AI as an afterthought.
Self-hosting with complete data control. For teams handling sensitive data, the self-hosted deployment provides data residency guarantees that hosted-only platforms cannot match.
Clean, accessible UI. The flow builder is more opinionated and less flexible than n8n's canvas, but it is significantly more approachable for non-technical users. Teams with mixed technical profiles can onboard more quickly to Activepieces than to n8n.
White-label and multi-tenant support. Few open-source automation platforms support agency/multi-tenant use cases this cleanly. For agencies building automation as a service, this is a significant feature.
Limitations#
Smaller piece library than Zapier or Make. More than 200 integrations is substantial for an open-source project but is still significantly fewer than Zapier's thousands of connectors. Teams with less common integration requirements may find gaps that require custom HTTP pieces or community contribution.
Task-based pricing on cloud plans can scale unexpectedly. Organizations that underestimate automation volume may find cloud plan costs growing faster than expected. Very high-volume automation use cases are often better served by self-hosting, where there are no per-task charges.
Less mature than n8n for complex enterprise deployments. n8n has a longer track record in enterprise self-hosted deployments, more community-contributed templates, and more mature documentation for complex deployment scenarios. Teams with demanding production requirements should assess the relative maturity.
AI Agent piece is early-stage. The AI Agent capability is powerful but less mature than dedicated agent platforms like Relevance AI or even Lindy AI. For teams whose primary goal is sophisticated agent automation (rather than traditional workflow automation augmented with AI), a purpose-built agent platform may be more appropriate.
Ideal Use Cases#
Development teams needing automation without Zapier costs. Engineering teams that want workflow automation for internal processes, CI/CD hooks, data synchronization, and notification routing without paying Zapier enterprise pricing find Activepieces a cost-effective self-hosted alternative.
Privacy-sensitive data automation. HR workflows (employee data processing), financial data synchronization, healthcare adjacent automation (appointment reminders, administrative workflows), and legal department automation where PII handling requires data to stay within organizational infrastructure.
Agencies building multi-client automation. The multi-tenant and white-label support make Activepieces a viable platform for agencies delivering automation solutions to clients, with client isolation and optional white-labeling.
Teams wanting AI-augmented automation without changing platforms. Organizations already using workflow automation who want to add LLM-based processing (classify incoming data, generate response drafts, extract structured data from documents) without adopting a separate AI platform can add AI pieces to existing Activepieces flows.
Bootstrapped businesses and startups. The free open-source tier provides full-featured automation without ongoing SaaS subscription costs — a meaningful advantage for early-stage companies managing costs carefully.
Getting Started#
Activepieces Cloud is the fastest onboarding path: create an account, build your first flow using the template library (organized by use case), and connect your first apps via OAuth. The flow builder tutorial walks through creating a basic trigger-action flow in under 10 minutes.
For self-hosting, the recommended starting point is the Docker Compose quick-start on the Activepieces documentation site. The single-server deployment requires Docker, Docker Compose, and approximately 2GB of RAM for comfortable operation. The setup process is well-documented and typically takes under 30 minutes for a working instance.
The AI pieces documentation covers model configuration (adding your OpenAI or Anthropic API key to Activepieces connections) and provides example flows for common AI automation patterns. For teams new to AI agent concepts, the how to build a research AI agent tutorial provides foundational understanding of the agent loop that the AI Agent piece implements.
Teams interested in training automation on proprietary knowledge should read the how to train an AI agent on your own data tutorial for context on knowledge base construction that complements Activepieces' AI capabilities.
How It Compares#
Activepieces vs Zapier. Zapier has far more integrations, stronger brand recognition, and more polish in the user experience. Activepieces offers self-hosting for data sovereignty, MIT open-source licensing with no vendor lock-in, and significantly lower cost at scale. For teams where cost or data residency are material concerns, Activepieces is the stronger choice. For teams that need maximum integration coverage and have no self-hosting capability, Zapier remains dominant. See the full n8n vs Make vs Zapier comparison for a detailed breakdown of automation platform options.
Activepieces vs n8n. n8n is the most established self-hosted automation platform and has a larger template library, more mature enterprise features (including its own fair-code license for self-hosting), and a more flexible free-form canvas. Activepieces' MIT license is more permissive than n8n's fair-code license, and Activepieces' AI integration is more developed. For teams that need maximum flexibility and maturity, n8n has the edge. For teams prioritizing MIT licensing, AI capabilities, and a more accessible UI, Activepieces is worth serious evaluation.
Activepieces vs Lindy AI. Lindy is a hosted-only, AI-native agent builder focused on personal productivity automation (email, calendar, CRM). Activepieces is a self-hostable workflow automation platform with AI capabilities added to a broader automation foundation. If the primary goal is AI agent automation and self-hosting is not a requirement, Lindy is faster to configure. If the goal is general workflow automation with AI capabilities and data sovereignty matters, Activepieces is more appropriate. See the Lindy AI review for comparison.
Bottom Line#
Activepieces is the most technically capable open-source workflow automation platform with meaningful native AI capabilities. Its MIT license, self-hosting architecture, active community, and AI piece library make it a compelling alternative to expensive SaaS automation platforms for teams that value data sovereignty and cost control.
The platform is best suited to technically capable teams (developers, DevOps, technically-minded operations) who are comfortable with self-hosted infrastructure and want to avoid vendor lock-in. It is not the right choice for teams that need maximum integration breadth immediately, very high-volume enterprise automation with SLA guarantees, or non-technical users who need a fully managed experience without infrastructure overhead.
For the right team profile, Activepieces offers a level of automation capability and control that proprietary platforms cannot match at comparable cost.
Browse more platform profiles in the AI Agents directory. Compare automation platforms in the n8n vs Make vs Zapier comparison.